The OpenDataSoft platform retrieves the default field labels found in the source dataset. It is however possible to change each dataset field label.

Note

We highly recommend to choose well-written, explicit labels. Also keep in mind that since these labels will be displayed in the front office for all portal users, it might be preferable to choose simple labels instead of business-specific terms, to make sure that the data can be understood by a wider audience.

To change a label:

In the preview area of the Processing tab, select the current label of the field of your choice.

Type a new label. It can contain special characters.

Click outside the label area or press Enter for the changes to be taken into account.

Caution

Changing the label of a field does not modify in any way the technical identifier of that field, which can be found in the Configuration menu of the dataset.

Field values are dates.
The ideal format is the ISO 8601 format, which is YYYY-mm-dd. Other formats are also understood by the platform, such as: YYYY/mm/dd or dd/mm/YYYY.

Note

The platform will try to guess as accurately as possible the input date format. However, in case of bad detection or ambiguity, use the Normalize Date processor to define the parsing format of the date field.

DateTime

Field values are a combination of a date and a time.
The ideal format is the ISO 8601 format, which is YYYY-mm-ddTHH:MM:ss+00:00, YYYY-mm-ddTHH:MM:ssZ or YYYYmmddTHHMMssZ. Other formats are also understood by the platform, such as: YYYY-mm-dd-HH:MM:ss or or YYYY-mm-ddHH:MM:ss.

Note

The platform will try to guess as accurately as possible the input datetime format. However, in case of bad detection or ambiguity, use the Normalize Date processor to define the parsing format of the datetime field.

Field values are decimal numbers.
Valid separators for the decimal part are . or ,.

Geo point

Field values are a single geographical location expressed in the format <LAT>,<LON>, for instance
45.8,2.5.

Note

If your dataset contains two fields, latitude and longitude, use the Create GeoPoint processor to create a valid geo point field.

Geo shape

Field values are geographical shapes expressed in GeoJSON. For example :

{"type":"LineString","coordinates":[[100.0,0.0],[101.0,1.0]]}

Note

Feature collections are not supported.

Integer

Field values are integer numbers.
If a floating point value is found, it is automatically cast to its integer part.

Text

Field values are textual data.

File

Field values are files sourced with one of the available methods to create a dataset with images (with the File processor, through an archive file or with a specific extractor), creating a field which default type is file. This field type is only available in that case.

Facets define the filters of a dataset, which are displayed on the left of the dataset’s visualization, in the front office. These filters have several purposes: they allow the users to find specific, precise records into a dataset, but they also allow the creation of charts afterward (if a field’s records are other than numbers, they will be usable in the Chart Builder and in the Analyze view only if they are set up as facets).

Note

Fields which type is either geo shape or geo point cannot be set up as facets.

To set up a field as a facet:

In the preview area of the Processing tab, choose the field you want to set up as a facet. Choose a field relevant enough to become a filter.

Technical identifier of the field. In contrary to the label, the technical identifier does not have aesthetic purposes and thus cannot contain special characters, including spaces. Technical identifiers can be used for instance when creating a custom tooltip with HTML.

Warning

Changing the technical identifier of a field could break reuses of the related dataset (custom tooltip, custom tab or pages). It could also be a problem if the source of the dataset is (regularly) updated: when replacing a source with a newer one, the platform checks the technical identifier of the fields of both sources in order to find a match between the two -then replacing the old data with the new ones. If technical identifiers are not the same anymore, the dataset cannot be updated.

To change the technical identifier of a field:

Select the current technical identifier of the field, written in the text box under “Name”.

Type a new technical identifier. It musn’t contain special characters.

Click outside the text box or press Enter for the change to be taken into account.

Unique ID

Each record is uniquely identified by its identifier, which is by default computed as the fingerprint of all the record fields values. If the Unique ID option is activated for a field, records with the same identifier (or value) are deleted for only the last/oldest one to stay in the dataset. It is most useful for real-time datasets, to make sure that instead of adding new records every time the dataset is updated, new values replace the old ones.

month: only the month and year of the date are displayed in the dataset

day: the full date (day, month and year) is displayed in the dataset

For datetime fields:

hour

minute

As for the datetime precisions, the full datetime (hour and minutes) is displayed in the dataset. The difference is in the Analyze view and in the Chart Builder where the degree of precision is available to configure the chart.

By default, only numerical fields (decimals and integers) are sortable. This option activates sorting on textual fields. It is then possible, when in the Table view of the dataset in the front office, to sort text fields in an alphabetical order.

To make a field sortable:
Tick the “Sortable” box.

Multivalued

This option is for multi-valued records separated by one same separator. Example: France,UK,USA When set up as a facet, each of the field’s records values appears as a separate entry in the filters section. When clicking on one of the entry, all the other entries which are not related (meaning the entries which never appear in the same record as part of a multi-values combination) automatically disappear -only the related entries remain as available filter entries.

To activate the multivalued option:

Tick the “Multivalued” box.

In the text box below, type the separator between the values of the records.

Click outside the text box or press Enter for the change to be taken into account.

Hierarchical

This option is for multi-valued records, separated by one same separator and which have a hierarchical relation. Example: France/Ile-de-France/Paris When set up as a facet, each first value of each record’s multi-values combination appears as a separate entry in the filters section. When clicking on one entry, all second-level values related to that entry appear, and so on. Example: After clicking on the filter entry France, the related second-level entry Ile-de-France appears. After clicking on Ile-de-France, the related third-level entry Paris appears.

To activate the hierachical option:

Tick the “Hierarchical” box.

In the text box below, type the separator between the values of the records.

Click outside the text box or press Enter for the change to be taken into account.

Dataset fields can be reordered in their dataset. It can have 2 kinds of impact:

In the filters section of the dataset, in the front office. Changing the order of the fields in the dataset also changes the order of the filters. The first facetted field of the dataset becomes the first displayed filter, and so on.

In case the dataset contains geo shape fields. The Map view cannot display more than one layer of geo shapes, the geo shapes layer displayed by default must thus be defined. To do so, the field containing the geo shapes to be displayed by default on the map must the ordered before all other geo shapes fields.

To reorder a field in a dataset:

In the preview area of the Processing tab, click on the button of the field you want to reorder in the dataset.

While maintaining the click on the Reorder button, drag the field to its new position in the dataset.

Once the field in its new position in the dataset, stop maintaining the click.

Dataset fields can be discarded from the dataset. It does not mean that the field is completely removed from the dataset but only deleted from the output. This is why, once the dataset is published, the discarded field will not be displayed in any visualization and if the dataset is exported, the discarded field will not be in the export.

To discard a field from a dataset:
Click on the button of the field you want to discard from the dataset.

Since discarded fields are not completely removed from the dataset, they can be restored at any time.

To restore a discarded field from a dataset:

In the preview area of the Processing tab, swipe to the right to go to the last fields of the datasets.

The discarded fields of the dataset appear at the very end of the dataset, they look like blank, grey columns named by their technical identifiers. Find those you want to restore.